Exact distributional analysis of online algorithms with lookahead

In online optimization, input data is revealed sequentially. Optimization problems in practice often exhibit this type of information disclosure as opposed to standard offline optimization where all information is known in advance. We analyze the performance of algorithms for online optimization with lookahead using a holistic distributional approach. To this end, we first introduce the performance measurement method of counting distribution functions. Then, we derive analytical expressions for the counting distribution functions of the objective value and the performance ratio in elementary cases of the online bin packing and the online traveling salesman problem. For bin packing, we also establish a relation between algorithm processing and the Catalan numbers. The paper shows that an exact analysis is strongly interconnected to the combinatorial structure of the problem and algorithm under consideration. Results further indicate that the value of lookahead heavily relies on the problem itself. The analysis also shows that exact distributional analysis could be used in order to discover key effects and identify related root causes in relatively simple problem settings. These insights can then be transferred to the analysis of more complex settings where the introduced performance measurement approach has to be used on an approximative basis (e.g., in a simulation-based optimization)

A matheuristic for customized multi-level multi-criteria university timetabling

Course timetables are the organizational foundation of a university’s educational program. While students and lecturers perceive timetable quality individually according to their preferences, there are also collective criteria derived normatively such as balanced workloads or idle time avoidance. A recent challenge and opportunity in curriculum-based timetabling consists of customizing timetables with respect to individual student preferences and with respect to integrating online courses as part of modern course programs or in reaction to flexibility requirements as posed in pandemic situations. Curricula consisting of (large) lectures and (small) tutorials further open the possibility for optimizing not only the lecture and tutorial plan for all students but also the assignments of individual students to tutorial slots. In this paper, we develop a multi-level planning process for university timetabling: On the tactical level, a lecture and tutorial plan is determined for a set of study programs; on the operational level, individual timetables are generated for each student interlacing the lecture plan through a selection of tutorials from the tutorial plan favoring individual preferences. We utilize this mathematical-programming-based planning process as part of a matheuristic which implements a genetic algorithm in order to improve lecture plans, tutorial plans, and individual timetables so as to find an overall university program with well-balanced timetable performance criteria. Since the evaluation of the fitness function amounts to invoking the entire planning process, we additionally provide a proxy in the form of an artificial neural network metamodel. Computational results exhibit the procedure’s capability of generating high quality schedules

Simulation-based multi-criteria decision making: an interactive method with a case study on infectious disease epidemics

Whenever a system needs to be operated by a central decision making authority in the presence of two or more conflicting goals, methods from multi-criteria decision making can help to resolve the trade-offs between these goals. In this work, we devise an interactive simulation-based methodology for planning and deciding in complex dynamic systems subject to multiple objectives and parameter uncertainty. The outline intermittently employs simulation models and global sensitivity analysis methods in order to facilitate the acquisition of system-related knowledge throughout the iterations. Moreover, the decision maker participates in the decision making process by interactively adjusting control variables and system parameters according to a guiding analysis question posed for each iteration. As a result, the overall decision making process is backed up by sensitivity analysis results providing increased confidence in terms of reliability of considered decision alternatives. Using the efficiency concept of Pareto optimality and the sensitivity analysis method of Sobol’ sensitivity indices, the methodology is then instantiated in a case study on planning and deciding in an infectious disease epidemic situation similar to the 2020 coronavirus pandemic. Results show that the presented simulation-based methodology is capable of successfully addressing issues such as system dynamics, parameter uncertainty, and multi-criteria decision making. Hence, it represents a viable tool for supporting decision makers in situations characterized by time dynamics, uncertainty, and multiple objectives

Patient-Centered Medicine and Self-Help Groups in Germany: Self-Help Friendliness as an Approach for Patient Involvement in Healthcare Institutions

Collaboration between laypersons and professionals is closely linked to the concept of patient centeredness. Patient centeredness means meeting the needs of individual patients as well as reacting to patients’ demands on the collective level. The support of self-help groups and their integration into healthcare institutions represent a major policy approach to fulfilling this requirement. Here, we first deal with the concept of patient centeredness in general, and the understanding of concept and use in Germany. We also provide a short definition of self-help friendliness (SHF) and discuss the success achieved in implementing it in Germany so far. We then clarify the closely related concepts of patient centeredness, patient participation and patient involvement SHF is seen as a strategy for increasing both patient centeredness and patient participation in healthcare services. We subsequently describe the involvement of self-help groups and patient associations in a series of empirical studies and practice-oriented projects carried out between 2004 and 2013. The last section contains a general discussion of the SHF approach as a means of systematically increasing sustainable patient centeredness and patient participation in healthcare services. Finally, we address the chances for future development in Germany and the transferability of SHF to other countries

Comparison of different approaches to multistage lot sizing with uncertain demand

We study a new variant of the classical lot sizing problem with uncertain demand where neither the planning horizon nor demands are known exactly. This situation arises in practice when customer demands arriving over time are confirmed rather lately during the transportation process. In terms of planning, this setting necessitates a rolling horizon procedure where the overall multistage problem is dissolved into a series of coupled snapshot problems under uncertainty. Depending on the available data and risk disposition, different approaches from online optimization, stochastic programming, and robust optimization are viable to model and solve the snapshot problems. We evaluate the impact of the selected methodology on the overall solution quality using a methodology-agnostic framework for multistage decision-making under uncertainty. We provide computational results on lot sizing within a rolling horizon regarding different types of uncertainty, solution approaches, and the value of available information about upcoming demands

Managing the intake of new patients into a physician panel over time

This article focuses on balancing supply and demand for physicians and panel patients on a tactical level to ensure a manageable workload for the physician and access to care for patients. Patients are part of the physician’s panel if they visit the physician somewhat regularly. For the first time, we propose deterministic integer linear programs that decide on the intake of new patients into panels over time, taking into account the future panel development. The main objective is to minimize the deviation between the expected panel workload and the physician’s capacity over time. We classify panel patients with respect to age and the number of visits in a period and assume a transition probability from one visit category to another from one period to the next. We can include stationary patient attributes and consider several physicians together. The programs work with aggregation levels for the new patients’ demand concerning the patient attributes. We conduct experiments with parameters based on real-world data. We consider the transition between visit categories and the new patients’ demand to be stochastic in a discrete-event simulation. We define upper bounds on the number of patients in a patient class to be accepted in a period through solving the programs several times with different demand inputs. Even in this uncertain environment, we can significantly reduce the expected differences between workload and capacity over time, taking into account several future periods instead of one. Using a detailed classification of new patients decreases the expected differences further

Influence of Ibuprofen on Phospholipid Membranes

Basic understanding of biological membranes is of paramount importance as these membranes comprise the very building blocks of life itself. Cells depend in their function on a range of properties of the membrane, which are important for the stability and function of the cell, information and nutrient transport, waste disposal and finally the admission of drugs into the cell and also the deflection of bacteria and viruses. We have investigated the influence of ibuprofen on the structure and dynamics of L-alpha-phosphatidylcholine (SoyPC) membranes by means of grazing incidence small-angle neutron scattering (GISANS), neutron reflectometry and grazing incidence neutron spin echo spectroscopy (GINSES). From the results of these experiments we were able to determine that ibuprofen induces a two-step structuring behavior in the SoyPC films, where the structure evolves from the purely lamellar phase for pure SoyPC over a superposition of two hexagonal phases to a purely hexago- nal phase at high concentrations. Additionally, introduction of ibuprofen stiffens the membranes. This behavior may be instrumental in explaining the toxic behavior of ibuprofen in long-term application.Comment: -Improved indexing in Fig. 4e) -changed concentrations to mol% -improved arguments, however conclusions stay unchange

Multifacility ordered median problems on networks: a further analysis

In this paper, we address the ordered p-median problem, which includes as special cases most of the classical multifacility location problems discussed in the literature. Finite dominating sets (FDS) are known for particular instances of this problem: p-median, p-center, and p-centdian. We find an FDS for the ordered p-median problem. This set allows us to gain a better insight into the general FDS structure of network location problems. This FDS is later used to present the first polynomial time algorithm for p-facility ordered median problems on tree networks

Location problems with multiple criteria

This chapter analyzes multicriteria continuous, network, and discrete location problems. In the continuous framework, we provide a complete description of the set of weak Pareto, Pareto, and strict Pareto locations for a general Q-criteria location problem based on the characterization of three criteria problems. In the network case, the set of Pareto locations is characterized for general networks as well as for tree networks using the concavity and convexity properties of the distance function on the edges. In the discrete setting, the entire set of Pareto locations is characterized using rational generating functions of integer points in polytopes. Moreover, we describe algorithms to obtain the solutions sets (the different Pareto locations) using the above characterizations. We also include a detailed complexity analysis. A number of references has been cited throughout the chapter to avoid the inclusion of unnecessary technical details and also to be useful for a deeper analysis